U.S. patent application number 13/812949 was filed with the patent office on 2013-05-23 for systems and methods for apportioning power consumption.
The applicant listed for this patent is Cullen E. Bash, Yuan Chen, Daniel J. Gmach, Mustazirul Islam, Jerome Rolia, SM Prakash Shiva, Zhikui Wang. Invention is credited to Cullen E. Bash, Yuan Chen, Daniel J. Gmach, Mustazirul Islam, Jerome Rolia, SM Prakash Shiva, Zhikui Wang.
Application Number | 20130132009 13/812949 |
Document ID | / |
Family ID | 45559714 |
Filed Date | 2013-05-23 |
United States Patent
Application |
20130132009 |
Kind Code |
A1 |
Rolia; Jerome ; et
al. |
May 23, 2013 |
SYSTEMS AND METHODS FOR APPORTIONING POWER CONSUMPTION
Abstract
The present disclosure includes a system and method for
apportioning power consumption. In an example of apportioning power
consumption according to the present disclosure, a transaction mix
for a service is determined (104, 204, 330, 420), component
resource usage for each of a number of components that are used
while completing the service is determined (106, 206, 108, 208,
422), and component power consumption for each of the number of
components is determined by use of the component resource usage
(334, 424).
Inventors: |
Rolia; Jerome; (Kanata,
CA) ; Bash; Cullen E.; (Los Gatos, CA) ;
Gmach; Daniel J.; (Palo Alto, CA) ; Chen; Yuan;
(Sunnyvale, CA) ; Islam; Mustazirul; (Rocklin,
CA) ; Shiva; SM Prakash; (Bangalore, IN) ;
Wang; Zhikui; (Fremont, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Rolia; Jerome
Bash; Cullen E.
Gmach; Daniel J.
Chen; Yuan
Islam; Mustazirul
Shiva; SM Prakash
Wang; Zhikui |
Kanata
Los Gatos
Palo Alto
Sunnyvale
Rocklin
Bangalore
Fremont |
CA
CA
CA
CA
CA |
CA
US
US
US
US
IN
US |
|
|
Family ID: |
45559714 |
Appl. No.: |
13/812949 |
Filed: |
August 6, 2010 |
PCT Filed: |
August 6, 2010 |
PCT NO: |
PCT/US2010/044728 |
371 Date: |
January 29, 2013 |
Current U.S.
Class: |
702/61 |
Current CPC
Class: |
G06F 1/3209 20130101;
G06F 1/329 20130101; G06F 2201/87 20130101; G06F 11/3003 20130101;
G06F 17/00 20130101; G06F 11/3062 20130101; G01R 21/133 20130101;
Y02D 10/00 20180101; Y02D 10/24 20180101; G06F 2201/865
20130101 |
Class at
Publication: |
702/61 |
International
Class: |
G01R 21/133 20060101
G01R021/133; G06F 17/00 20060101 G06F017/00 |
Claims
1. A method for apportioning power consumption, the method
comprising: determining a transaction mix for a service (104, 204,
330, 420); determining component resource usage for each of a
number of components that are used while completing the service
(106, 206, 108, 208, 422); and determining component power
consumption for each of the number of components by using the
component resource usage (334, 424).
2. The method of claim 1, wherein determining the transaction mix
for the service (104, 204 330, 420) includes determining each
transaction type (104, 204) in the service and a request rate for
each transaction type.
3. The method of claim 2, wherein determining component resource
usage (106, 206, 108, 208, 422) includes summing the product of a
component's resource demand for each transaction type (104, 204)
and the request rate for each transaction type of the transaction
mix (104, 204) for the service.
4. The method of claim 1, wherein determining component power
consumption for each of the number of components (334, 424)
includes determining power impact factors for each of the number of
components used in the service.
5. The method of claim 1, wherein method includes determining power
consumption for the service (426) by aggregating component power
consumption for each of the number of components.
6. The method of claim 1, wherein determining component resource
usage for each of a number of components (334, 424) using the
transaction mix (104, 204) includes determining background resource
usage for each of the number of components.
7. The method of claim 1, wherein determining component power
consumption for each of the number of components (334, 424)
includes determining the background power consumption for each of
the number of components.
8. A non-transitory computer readable medium (593) having
instructions stored thereon executable by a processor (592) to:
determine power consumption for a service (426), wherein power
consumption for the service includes an aggregate of component
power consumption (334, 424) for each of a number of components
(106, 206) used in the service and wherein component power
consumption is a function of component resource usage and a
transaction mix for the service.
9. The non-transitory computer readable medium (593) of claim 8,
wherein the service includes a service selected from the group
consisting of logging data, browsing data, and adding data.
10. The non-transitory computer readable medium (593) of claim 8,
wherein the number of components (106, 206) include components
selected from the group consisting of a web server, an application
server, and a database server (584).
11. The non-transitory computer readable medium (593) of claim 8,
wherein the transaction mix for the service includes each
transaction type (104, 204) in the service and a request rate for
each transaction type (104, 204).
12. The non-transitory computer readable medium (593) of claim 11,
wherein a resource demand of each transaction executed by the
component is determined by a linear regression of data that
includes resource demand data for each component.
13. The non-transitory computer readable medium (593) of claim 12,
wherein component resource usage includes a sum of the product of
the resource demand of each transaction executed by a component and
the request rate for each transaction type executed by the
component.
14. A power consumption apportioning system, comprising: a number
of communicatively coupled user computing devices (587, 588, 584);
and at least one server computing device communicatively coupled to
the number of user computing devices (587, 588, 584), and having:
at least one processor (592); non-transitory memory (593) in
communication with the at least one processor, the non-transitory
memory (593) being programmed with instructions executable on the
at least one processor (592) to: determine power consumption for a
service (426) that uses a number of components by aggregating
component power consumption (334, 424) for each of the number of
components, and wherein component power consumption (334, 424) for
each of the number of components (106, 206) is determined by using
a transaction mix for the service and determining component
resource usage for each of the number of components.
15. The power consumption apportioning system of claim 14, wherein
component power consumption (334, 424) includes a sum of the
product of a resource demand of each transaction executed by each
of the number of components and a request rate for each transaction
type (104, 204) executed by each of the number of components.
Description
BACKGROUND
[0001] Energy efficiency is a concern in operating and managing
computing services. Energy consumption can affect the operational
costs for the computing services and can contribute to the
environmental impact of computing services. Power-aware service
management solutions require access to power consumption data at
the service level The power consumption of a computing service can
be a useful tool in devising methods to improve energy efficiency
for a computing service.
[0002] Deriving power consumption data for computing services can
be a challenging task. Computing services, such as customer
relationship management and electronic commerce services, can be
complex and include many service components running across multiple
physical servers. Service components from different services can be
co-located on a node and share resources on the node. In
particular, virtual server environments can include configurations
where components and resources for a computing service are shared
among one or more physical servers. Therefore, directly measuring
power consumption for a computing service at a service level can be
difficult and many times can be impossible.
[0003] In some previous approaches, power models have be used to
estimate power consumption. The power consumption estimates can use
resource usage in the power models, but these estimations can be
difficult because resources can be shared by multiple computing
services. Some previous approaches have used physical system level
power data to estimate power consumption, but these estimates can
not be used to determine power consumption at the service level
because physical system level power data does not include enough
granularity to determine the individual services that contribute
the power consumption of the system.
BRIEF DESCRIPTION OF THE DRAWINGS
[0004] FIG. 1 is a computing operation relationship diagram
illustrating business computing services, transactions, components,
and resources according to examples of the present disclosure.
[0005] FIG. 2 is a computing operation relationship diagram
illustrating components and resources in a computing transaction
according to examples of the present disclosure.
[0006] FIG. 3 is a method flow diagram illustrating apportioning
power consumption of a number of components to a computing service
according to examples of the present disclosure.
[0007] FIG. 4 is a block diagram illustrating determining power
consumption of a computing service 400 according to examples of the
present disclosure.
[0008] FIG. 5 is a computing network system according to examples
of the present disclosure.
DETAILED DESCRIPTION
[0009] The present disclosure includes a system and method for
apportioning power consumption. A method for apportioning power
consumption can include determining a transaction mix for a
service, determining component resource usage for each of a number
of components that are used while completing the service, and
determining component power consumption for each of the number of
components by using the component resource usage. The method can
further include determining each transaction type in the service
and the request rate for each transaction type, determining power
impact factors for each of the number of components used in the
service, and determining component resource usage by summing the
product of a component's resource demand for each transaction type
and the request rate for each transaction type of the transaction
mix for the service. Examples of the present disclosure can also
include determining power consumption for the service by
aggregating component power consumption for each of the number of
components.
[0010] In the following detailed description of the present
disclosure, reference is made to the accompanying drawings that
form a part hereof, and in which is shown by way of illustration
how examples of the disclosure may be practiced. These examples are
described in sufficient detail to enable those of ordinary skill in
the art to practice this disclosure, and it is to be understood
that other examples may be utilized and that process, electrical,
and/or structural changes may be made without departing from the
scope of the present disclosure. As used herein, the designators
"N," "M," "P,", "R," "S," "T," "U," and "V," particularly with
respect to reference numerals in the drawings, indicate that a
number of the particular feature so designated can be included with
examples of the present disclosure. The designators can represent
the same or different numbers of the particular features.
[0011] The figures herein follow a numbering convention in which
the first digit or digits correspond to the drawing figure number
and the remaining digits identify an element or component in the
drawing. Similar elements or components between different figures
may be identified by the use of similar digits. For example, 104
may reference element "04" in FIG. 1, and a similar element may be
referenced as 204 in FIG. 2. Elements shown in the various figures
herein can be added, exchanged, and/or eliminated so as to provide
a number of additional examples of the present disclosure. In
addition, the proportion and the relative scale of the elements
provided in the figures are intended to illustrate the examples of
the present disclosure, and should not be taken in a limiting
sense.
[0012] FIG. 1 is a computing operation relationship diagram
illustrating computing services, transactions, components, and
resources according to examples of the present disclosure. In a
computing network, services such as logging data, browsing data,
and requesting data, among other services, can be requested by a
user. These services can be completed by executing a number of
transactions using components, such servers, on a computing
network. A number of components can be included in a computing
device that can have a number of resources. The component resources
can be portions of a component that provide for the functional
operation of the component. The component resources consume power
while executing transactions. Component resources can include a
number of processors, a number of network interfaces, a number of
input/output (IO) interfaces, hard disk operation, and memory
operation, among other component resources. The power consumed
during a service by the components while completing the service is
a factor that can affect the cost of a service and is desirable to
know. The following discussion will be made in the context of a
computing service that uses servers and computing devices to
execute the service. However, examples of the present disclosure
are not limited to these examples, and the system and method of the
present disclosure may be implemented in many other configurations,
and applied to many other services that use power consuming
components.
[0013] in FIG. 1, computing operations can include a number of
services 102-1, . . . , 102-N. The services 102-1, . . . , 102-N
can include logging data, browsing data, and requesting data, among
other services. The services 102-1, . . . 102-N can include a
number of transactions 104-1, 104-M, 104-P, . . . , 104-R. The
transactions 104-1, 104-M, 104-P, . . . 104-R can include
operations that are performed by components on a network to execute
a service 102-1, . . . 102-N. A service can include any number of
types of transactions and any number of each type of transaction.
The type of the transaction and the number of each transaction type
and/or rate of each transaction type that make up a service can be
referred to as the transaction mix for a service.
[0014] In FIG. 1, the transaction mix for service 1 102-1 includes
transaction 1 104-1, transaction 2 104-2, and transaction M 104-M.
The transaction mix for service 2 102-1 includes transaction 1
104-1, transaction 3 104-3, and transaction P 104-P. The
transaction mix for service N 102-N includes transaction 2 104-2,
transaction 4 104-4, and transaction R 104-R. Each of the
transactions types, transaction 1 104-1, transaction 2 104-2,
transaction 3 104-3, transaction 4 104-4, transaction M 104-M,
transaction P 104-P, and transaction R 104-R, for each of the
services, service 1 104-1, service 2 102-2, and service N 104-N,
include a transaction rate for the transaction type of a given
service. The transaction mix, which includes the transaction rate
for each transaction type of a service, for each service can be
used to calculate the component resource usage for the components
used while completing a service.
[0015] A service is completed by executing the transaction mix for
the service on a number of components. The components can be
servers on a network, such as a web server, an application server,
a database server, and/or a computer. In FIG. 1, a number of
components, component 1 106-1, component 2 106-2, and component S
106-S, are illustrated. Each of the number of components include a
number of resources, such as a processor, a network interface, an
IO interface, hard disk operation, and memory operation, among
other component resources. A component's resource can be shared
among a number of computing devices. In FIG. 1, component 1 106-1
includes resource 1 108-1, resource 2 108-2, and resource T 108-T.
The resources for component 2 106-1 include resource 1 108-1,
resource 2 108-2, and resource U 108-U. The resources for component
S 106-S include resource 1 108-1, resource 2 108-2, and resource V
108-V. Each component can include a number of resources that may or
may not be used while executing a transaction of a service. A
service's resource usage is the sum of its transactions' resource
usage. A service's power usage is the sum of its transactions'
power usage. Transaction resource usage and power usage cannot
always be measured directly, but may be estimated using the method
described below.
[0016] FIG. 2 is a computing operation relationship diagram
illustrating components and resources in a computing transaction
according to examples of the present disclosure. In FIG. 2,
transaction M 204-M includes using component 1 206-1 and component
2 206-2 to execute transaction M 204-M. In some examples, component
1 206-1 could be a web server, component 2 206-2 could be a
database server, and transaction M 204-M could be a data request
for a browsing data service request from a user.
[0017] When transaction M 204-M is executed by component 1 206-1
and component 2 206-2, a number of component resources are used.
Component 1 206-1 uses resource 1 208-1 and resource 2 208-2 and
component 2 206-2 uses resource 2 208-2 and resource U 208-U. The
rate at which the resources are used during execution of a
transaction and the demand of each resource can be used to
determine the component resource usage for the components that are
used while executing a service. The component resource usage for a
service measures the amount that a component resource is used
during completion of a service.
[0018] FIG. 3 is a method flow diagram illustrating apportioning
the power consumption of a number of component's resources to a
computing service according to examples of the present disclosure.
A computing service can use a number of components that include a
number of resources that consume power. FIG. 3 illustrates a method
for apportioning the power consumption of the component's resources
that were used in completing the service to the service. In FIG. 3,
apportioning power consumption 300 includes determining a
transaction mix for a service 330, determining component resource
usage for each of a number of components that are used while
completing the service 332, and determining component power
consumption for each of the number of components by using the
component resource usage 334.
[0019] Apportioning the power consumption of a number of
component's resources to a computing service can further include
determining each transaction type in the service and the request
rate for each transaction type, determining power impact factors
for each of the number of components used in the service, and
determining component resource usage by summing the product of a
component's resource demand for each transaction type and the
request rate for each transaction type of the transaction mix for
the service. Examples of the present disclosure can also include
determining power consumption for the service by aggregating
component power consumption for each of the number of
components.
[0020] FIG. 4 is a block diagram illustrating determining power
consumption of a computing service 400 according to examples of the
present disclosure. In FIG. 4, determining power consumption of a
computing service 400 includes transaction metrics extraction 420.
Transaction metric extraction 420 includes determining the
transaction mix for a service. Transaction metrics for a service
can include the types of transactions that are part of the service
and the rate at which each transaction type is requested and/or
completed. As discussed above, the transaction mix includes the
type of the transactions (.lamda..sub.1, .lamda..sub.2, . . . ,
.lamda..sub.N), where N is the number of unique transaction types
and .lamda..sub.1 is the rate of each transaction type that make up
a service. The transaction metrics can be extracted from monitoring
data on a network. Transaction metrics for a service can include
the types of transactions that are part of the service and the rate
at which each transaction type is requested.
[0021] In examples of the present disclosure, if the transaction
types for a service are not given in the transaction metrics, a
classifier can be constructed to map the transactions based on the
resource demand for each transaction of a service. In examples the
present disclosure, the transaction metrics for the most popular
transactions can be used to create the transaction mix. In some
examples, the top 50 transaction types and rates may be used to
create the transaction mix because they may account for some
portion, e.g., 98%, of the resource demand for a component when
completing a service, which provides a significant sample of the
resource demand for a component allowing for a meaningful
calculation of the component resource usage.
[0022] In FIG. 4, determining power consumption of a computing
service 400 includes service component resource usage calculation
422. The resource demands of different transaction types are
usually different, but the resource demands of a single transaction
type is relatively fixed irrespective of the transaction mix of the
workload, since each transaction type usually has a relatively
fixed code execution path. The service component resource usage
calculation 422 uses the transaction mix that was created by the
transaction metrics extraction 420. The component resource usage
(U.sub.c) for each component used during a service is calculated by
summing the product of the transaction rate for each transaction
type and the resource demand for each transaction type
(.alpha..sub.i) and adding the background resource usage
(U.sub.c,0) to the sum. The background resource usage is the
resource usage when there are no transactions being executed. The
component resource usage (U.sub.c) for a component c can be defined
by the following equation:
U c = i = 1 N .alpha. i .lamda. i + U c , 0 ##EQU00001##
The resource demand for each transaction type (.alpha..sub.i) and
the background resource usage (U.sub.c,0) can be calculated by
linear regression from a number of measurements of transaction mix
and its corresponding measured U.sub.c. The measurements may
include the resource usage of the component when no transactions
are being executed.
[0023] In examples of the present disclosure, an aggregate resource
usage model for a service can be created by summing the component
resource usage calculation for each component and adding the
background load on the node that each component is coupled to in a
network.
[0024] The resource usage for each component used during a service
may be relatively static across different transaction mixes and may
be independent of other service components on the same server. The
resource usage calculation for a component can be recalibrated
based on measured transaction mix and estimates for .alpha..sub.i
and U.sub.c,0 if there are non-stationary changes to the workload
on the component. Data can be gathered for the changed transaction
mix and resource demand operations and used to periodically
recalculate the component resource demand for a service and
background resource usage.
[0025] In examples of the present disclosure, a component resource
usage can be calculated by adding the background resource usage
(U.sub.c,0) for a component to the product of an aggregate
transaction rate for a component and an aggregate resource demand
for a component. This component resource usage calculation can be
used when the transaction mix for a service is not known or when
the transaction mix is relatively stationary for a service.
[0026] In FIG. 4, determining power consumption of a computing
service 400 includes service component power calculation 424. The
service component power (P.sub.c) calculation 424 uses the service
component resource usage (U.sub.c) calculation and power impact
factors for each component. Power impact factors .rho., .beta.,
.gamma., and .THETA. for each component resource can be calculated
by linear regression of data that includes power data for each of
the resources. Component resources can include a processor, a
network input/output (IO) interface, hard disk operation, and
memory operation, among other component resources. The service
component power consumption (P.sub.c) for each component used
during a service can be calculated by summing the product of the
component resource usage (U.sub.c) and the power impact factor for
each resource and adding the background power consumption (P.sub.b)
to the sum. The background power consumption (P.sub.b) is the power
consumption when none of the resources are being used to execute a
transaction. The background power consumption can be calculated by
linear regression of measurements of the power consumed by each
resource when no transactions are being executed. In examples of
the present disclosure, the power impact factors can be updated at
periodic intervals by measuring the power consumption in real time.
The service component power consumption (P.sub.c) for each
component used during a service can be can be defined by the
following equation:
P.sub.c=P.sub.b+.rho.U.sub.c1+.beta.U.sub.c2+.gamma.U.sub.c3.theta.U.sub-
.c4
where .rho., .beta., .gamma., and .THETA. are power impact factors
for a processor, memory, disk IO, and network IO, respectively, and
U.sub.c1, U.sub.c2, U.sub.c3, and U.sub.c4 are processor usage,
memory usage, disk IO usage, and network IO usage, respectively. In
some examples, the quantity of memory used may be included in the
baseline power consumption P.sub.b, In other examples, the quantity
of memory used may be expressed as another term used to compute
P.sub.c.
[0027] In examples of the present disclosure, the processor
resource is the major power consumer for a component and using just
the processor power consumption in the service component power
calculation 424 provides an accurate model of the power consumed by
a component during a service. In examples of the present
disclosure, a number of components can be on a node. Therefore, a
node with a number of components can be used to complete a number
of services, some even simultaneously. The background power
consumption for the node, which includes a number of components,
can be apportioned among the components that share the node. One
method to apportion the background power consumption is to assign
the same proportion of component resource usage to resource usage
of the node to the background power consumption for a component.
Another method to apportion the background power consumption is to
assign the background power consumption for a component as the
component resource usage multiplied by the background power
consumption for the node and add that to the product of the
remaining, i.e., unaccounted for, background power consumption for
the node multiplied by the ratio of the difference between peak and
average resource usage for the component and the sum of the
difference between peak and average resource usage for all the
components on the node. The peak resource usage is the
100-percentile of resource usage for a component. in other
examples, another percentile, such as the 95-percentile of resource
usage could also be used in the same manner.
[0028] in FIG. 4, apportioning power consumption includes service
power calculation 426. Service power calculation 426 includes
summing the service component power calculation 424 for each
component of the service. The service configuration can be used to
determine the components that are used in completing a service.
[0029] In examples of the present disclosure, the power consumption
for service can be calculated by determining the transaction mix
for a service, using the transaction mix to determine the component
resource usage for a service, using the component resource usage
for a service to determine the component power consumption for a
service, and summing power consumption for each component used in a
service. The examples of the present disclosure can quantify the
power consumption of a service while taking into account that
services can have an impact on a components power consumption that
is greater than just the power increase through direct resource
demand of the service components used in a service.
[0030] Examples of the present disclosure can also provide a
process model for a service that includes component resource usage
models, component power consumption models, monitoring data, and
service configuration data to obtain the service power
consumption.
[0031] FIG. 5 is a computing network system 583 according to
examples of the present disclosure. The computing network system
583 can include a communication network 585 having a number of
electronic devices communicatively coupled thereto. As shown in
FIG. 5, communication network 585 can have a first mobile device
590, a first user device 587, a second user device 588, a first
server 584-1, a second server 584-2, and a third server 584-3
communicatively coupled to network 585. Each system component can
be coupled to network 585 by a wired or wireless communication
channel. In FIG. 5, the first mobile device 590 is shown being
coupled to the network 585 by a first communication channel 596;
first user device 587 is shown being coupled to the network 585 by
a second communication channel 597; second user device 588 is shown
being coupled to the network 585 by a third communication channel
598; first server 584-1 is shown being coupled to the network 585
by a fourth communication channel 599; second server 584-2 is shown
being coupled to the network 585 by a fifth communication channel
591; and third server 584-3 is shown being coupled to the network
585 by a sixth communication channel 594.
[0032] Not all of the components and/or communication channels
illustrated in FIG. 5 are required to practice the system and
method of the present disclosure, and variations in the
arrangement, type, and quantities of the components may be made
without departing from the spirit or scope of the system and method
of the present disclosure. Other computing network system
components can include personal computers, laptop computers, mobile
devices, cellular telephones, personal digital assistants, video
game consoles, or the like. Communication channels may be similar
to, or different from, other communication channels.
[0033] Generally, mobile device 590, and first and second user
devices 587 and 588, and first, second, and third servers 584-1,
584-2, and 584-3 may include virtually any computing device capable
of connecting to another computing device to send and receive
information, including web requests for information from a server
device, and the like.
[0034] Mobile device 590 and the first and second user devices 587
and 588 may further include a client application to manage various
actions, for example, a web browser application to enable an
end-user to interact with one or more servers (e.g., server 584)
and/or other devices and/or applications via network 585.
[0035] Servers 584-1, 584-2, and 584-3 may include a server
application to manage various actions, for example, a web-server
application to enable an end-user to interact with servers 584-1,
584-2, and 584-3 via network 585. In examples of the present
disclosure, mobile device 590, first and second user devices 587
and 588, and servers 584-1, 584-2, and 584-3 may complete a
computing service by executing the transactions that make up a
service. In FIG. 5, first user device 587 includes a processor 592
and a non-transitory computer readable medium 593 for executing
instructions. Mobile device 590, first and second user devices 587
and 588, and servers 584-1, 584-2, and 584-3 can include a number
of processors and non-transitory computer-readable media (e.g.,
memory) that store instructions executable by the number of
processors. That is, the executable instructions can be stored in a
fixed tangible medium communicatively coupled to the one or more
processors. Memory can include RAM, ROM, and/or mass storage
devices, such as a hard disk drive, tape drive, optical drive,
solid state drive, and/or floppy disk drive.
[0036] The non-transitory computer-readable media can be programmed
with instructions such as an operating system for controlling the
operation of servers 584-1, 584-2, and 584-3, and/or computing
services such as logging data, browsing data, and requesting data,
among other services. The operating system and/or applications may
be implemented as one or more executable instructions stored at one
or more locations within volatile and/or non-volatile memory.
Servers 584-1, 584-2, and 584-3 may also include an internal or
external database, or other archive medium for storing, retrieving,
organizing, and otherwise managing computing services.
[0037] Mobile device 590 can also be a user device and include a
processor in communication with a non-transitory memory, a power
supply, a number of network interfaces, an audio interface, a video
interface, a display, a keyboard and/or keypad, and an optional
global positioning systems (GPS) receiver. Mobile device 590 may
optionally communicate with a base station (not shown), or directly
with another network component device. Network interfaces include
circuitry for coupling the mobile device to a number of networks,
and is constructed for use with a number of communication protocols
and technologies including, but not limited to, e-mail, Internet,
and/or wireless communication protocols. The network interface is
sometimes known as a transceiver, transceiving device, or network
interface card (NIC).
[0038] Applications on client devices may include computer
executable instructions stored in a non-transient medium which,
when executed by a processor, provide functions, such as a web
browser, to enable interaction with other computing devices such as
a server, and/or the like.
[0039] In some examples, the above discussed computing network
system can be used, controlled, and/or the like through a web
browser by a user. In some examples, the web browser can
communicate with a web server running server-side computing
applications to perform computing services.
[0040] The above specification, examples and data provide a
description of the method and applications, and use of the system
and method of the present disclosure. Since many examples can be
made without departing from the spirit and scope of the system and
method of the present disclosure, this specification merely sets
forth some of the many possible configurations and
implementations.
[0041] Although specific examples have been illustrated and
described herein, those of ordinary skill in the art will
appreciate that an arrangement calculated to achieve the same
results can be substituted for the specific examples shown. This
disclosure is intended to cover adaptations or variations of a
number of examples of the present disclosure. It is to be
understood that the above description has been made in an
illustrative fashion, and not a restrictive one. Combination of the
above examples, and other examples not specifically described
herein will be apparent to those of skill in the art upon reviewing
the above description. The scope of the number of examples of the
present disclosure includes other applications in which the above
structures and methods are used. Therefore, the scope of number of
examples of the present disclosure should be determined with
reference to the appended claims, along with the full range of
equivalents to which such claims are entitled.
[0042] Various examples of the system and method for apportioning
power consumption have been described in detail with reference to
the drawings, where like reference numerals represent like parts
and assemblies throughout the several views. Reference to various
examples does not limit the scope of the system and method for
displaying advertisements, which is limited only by the scope of
the claims attached hereto. Additionally, any examples set forth in
this specification are not intended to be limiting and merely set
forth some of the many possible examples for the claimed system and
method for apportioning power consumption.
[0043] Throughout the specification and claims, the meanings
identified below do not necessarily limit the terms, but merely
provide illustrative examples for the terms. The meaning of "a,"
"an," and "the" includes plural reference, and the meaning of "in"
includes "in" and "on." The phrase "in an example," as used herein
does not necessarily refer to the same example, although it
may.
[0044] In the foregoing Detailed Description, some features are
grouped together in a single example for the purpose of
streamlining the disclosure. This method of disclosure is not to be
interpreted as reflecting an intention that the disclosed examples
of the present disclosure have to use more features than are
expressly recited in each claim. Rather, as the following claims
reflect, inventive subject matter lies in less than all features of
a single disclosed example. Thus, the following claims are hereby
incorporated into the Detailed Description, with each claim
standing on its own as a separate example.
* * * * *